Accurate location of anatomical landmarks, such as ligament attachment points, in patient image data is critical to the overall outcome of patient-matched instrumentation techniques. Ligament attachment points can be used to facilitate consistent placement of implants on a patient's bone and may offer surgeons a reliable frame of reference for properly orienting implants. However, the location of ligament attachment points may not be known by a surgeon before a surgical operation and may need to be assessed intraoperatively. Noninvasive imaging techniques, such as MRI scans and CT scans, allow image data representing a patient's joint to be collected in advance of a surgical procedure. However, it can be difficult to use the raw image data collected from preoperative imaging to provide a surgeon with accurate preoperative information about the location of ligament attachment points.
The location of anatomical landmarks in such image data is evaluated using 2-D slices within the orthogonal planes of a 3-D volume (e.g., coronal, sagittal, and axial planes). This approach provides suboptimal visualization of ligament attachment points that are not adequately depicted in any of these planes. As a result, identifying such attachment points (e.g. attachments points on epicondyles) is a time-consuming process and suffers from high inter-operator variability. Therefore, to facilitate accurate preoperative location of ligament attachment points, there is a need for improved visualization of ligament attachment points.